ADR-0002: Technology Stack Rationale

“The best tool for the job is the one you know how to use.” — Unknown

Status

Accepted

Context

When designing the seedling template, we need to choose the optimal technology stack for modern Python development. Each tool choice has significant implications for developer experience, performance, and maintainability.

Decision

Select specific technologies based on performance, developer experience, and modern Python best practices.

Consequences

Copier vs Cookiecutter

Why Copier?

  • Jinja2 templating: More powerful than Cookiecutter’s limited templating engine

  • Better dependency management: Handles template updates and dependencies more effectively

  • Modern Python support: Built with modern Python practices and type hints

  • Version control integration: Better git integration and update handling

  • Conditional templating: Advanced logic for conditional file generation

  • Template inheritance: Support for template inheritance and composition

Cookiecutter Limitations

  • Limited templating: Basic Jinja2 features only

  • Update challenges: Difficult to update existing projects

  • Python 2 legacy: Originally designed for Python 2

  • Limited extensibility: Harder to extend with custom logic

uv vs pip/poetry

Why uv?

  • Performance: 10-100x faster than pip for dependency resolution

  • Lockfile advantages: Reproducible builds with uv.lock

  • Modern Python tooling: Built for modern Python development

  • Modern Python tooling: Built specifically for modern Python development

  • Cross-platform: Works consistently across all platforms

  • Single tool: Replaces pip, virtualenv, and other tools

pip Limitations

  • Slow dependency resolution: Can take minutes for complex projects

  • No lockfile: Reproducible builds require additional tools

  • Limited caching: Less effective caching mechanisms

  • Platform differences: Different behavior across platforms

poetry Limitations

  • Complexity: Over-engineered for many use cases

  • Lockfile issues: Sometimes produces inconsistent lockfiles

  • Performance: Slower than uv for dependency resolution

  • Limited extensibility: Harder to extend with custom logic

Nox vs tox

Why Nox?

  • Python-native: Built specifically for Python projects

  • Session management: Clean separation of different tasks

  • CI integration: Perfect integration with GitHub Actions

  • Extensible: Easy to add new sessions and tasks

  • Modern design: Built with modern Python practices

  • Better error handling: More informative error messages

tox Limitations

  • Complex configuration: Overly complex for simple use cases

  • Legacy design: Built for older Python development patterns

  • Limited extensibility: Harder to extend with custom logic

  • Performance: Slower than Nox for many operations

Just vs Make

Why Just?

  • Cross-platform compatibility: Works on Windows, macOS, and Linux

  • Dependency management: Handles task dependencies automatically

  • Readability: Simple, readable syntax

  • No dependencies: Single binary, no Python installation required

  • IDE integration: Works well with modern IDEs

  • Modern design: Built with modern development practices

Make Limitations

  • Unix-centric: Primarily designed for Unix-like systems

  • Complex syntax: Arcane syntax and rules

  • Limited Windows support: Poor support on Windows

  • No dependency management: Manual dependency specification

  • Legacy tool: Designed for C/C++ development

Sphinx vs MkDocs

Why Sphinx?

  • Documentation standards: Industry standard for Python documentation

  • Extensibility: Rich ecosystem of extensions

  • Hosting integration: Perfect for GitHub Pages deployment

  • Search functionality: Built-in search capabilities

  • Versioning: Support for multiple documentation versions

  • API documentation: Excellent autodoc support

MkDocs Limitations

  • Limited extensibility: Fewer extensions available

  • Markdown only: Limited to Markdown format

  • Less Python-specific: Not designed specifically for Python

  • Limited API docs: Poor support for API documentation

  • Search limitations: Less powerful search functionality

pre-commit-ci vs Manual Enforcement

Why pre-commit-ci?

  • Automated quality enforcement: Runs quality checks on every PR

  • Team collaboration: Ensures consistent code quality across team

  • Auto-fix capabilities: Automatically fixes formatting issues

  • GitHub integration: Seamless integration with GitHub workflows

  • Configurable: Flexible configuration for different project needs

  • Free for public repos: No cost for public repositories

Manual Enforcement Limitations

  • Human error: Relies on developers remembering to run checks

  • Inconsistent: Different developers may use different tools

  • Time-consuming: Manual process takes time and effort

  • No guarantees: No guarantee that quality checks are run

  • Team coordination: Difficult to coordinate across team

Implementation Strategy

Phased Rollout

  1. Phase 1: Core template with basic functionality

  2. Phase 2: Advanced features and optimizations

  3. Phase 3: Enterprise features and integrations

Migration Path

  • From Cookiecutter: Clear migration guide and tools

  • From pip: Gradual migration with uv compatibility

  • From tox: Direct replacement with Nox

  • From Make: Simple Justfile conversion

Training and Documentation

  • Comprehensive documentation: Detailed guides for each tool

  • Video tutorials: Step-by-step video guides

  • Community support: Active community and support channels

  • Best practices: Documented best practices and patterns

References